The melanoma tumor glyco-code impacts human dendritic cells’ functionality and dictates clinical outcomes

Subversion of immunity is a hallmark of cancer development. Dendritic cells (DCs) are strategic immune cells triggering anti-tumor immune responses, but tumor cells exploit their versatility to subvert their functions. Tumor cells harbor unusual glycosylation patterns, which can be sensed through glycan-binding receptors (lectins) expressed by immune cells that are crucial for DCs to shape and orientate antitumor immunity. Yet, the global tumor glyco-code and its impact on immunity has not been explored in melanoma. To decrypt the potential link between aberrant glycosylation patterns and immune evasion in melanoma, we investigated the melanoma tumor glyco-code through the GLYcoPROFILE™ methodology (lectin arrays), and depicted its impact on patients’ clinical outcome and DC subsets’ functionality. Specific glycan patterns correlated with clinical outcome of melanoma patients, GlcNAc, NeuAc, TF-Ag and Fuc motifs being associated with poor outcome, whereas Man and Glc residues elicited better survival. Strikingly, tumor cells differentially impacting cytokine production by DCs harbored distinct glyco-profiles. GlcNAc exhibited a negative influence on cDC2s, whereas Fuc and Gal displayed inhibitory impacts on cDC1s and pDCs. We further identified potential booster glycans for cDC1s and pDCs. Targeting specific glycans on melanoma tumor cells restored DCs’ functionality. The tumor glyco-code was also linked to the nature of the immune infiltrate. This study unveils the impact of melanoma glycan patterns on immunity, and paves the way for innovative therapeutic options. Glycans/lectins interactions arise as promising immune checkpoints to rescue DCs from tumor’ hijacking to reshape antitumor immunity and inhibit immunosuppressive circuits triggered by aberrant tumor glycosylation.

3 respectively. Collected panDCs were stimulated for 5 hours with or without  and the production of cytokines was assessed by intracellular cytokine staining using flow cytometry. PanDCs were co-cultured for 20 hours with "positive" or "negative" tumor cell lines previously cultured or not with single or mixture of soluble lectins (blocking specific glycans) for 2 hours.
Collected panDCs were then stimulated for 5 hours with or without TLR-L (polyI:C, R848) and cytokines' production was measured using flow cytometry. The comparison of cytokine production with and without lectins allows deciphering the involvement of specific glycans in triggering or inhibiting DCs' functionality.

further boosted their good impact on cytokine production by cDC1s and pDCs
PanDCs were co-cultured for 20 hours with "positive" tumor cell lines previously cultured or not with soluble lectins for 2 hours. Collected panDCs were then stimulated for 5 hours with or without TLR-L (polyI:C, R848) and cytokines' production was measured using flow cytometry. Proportions of TNFα + cDC1s (left panels) and TNFα + pDCs (right panels) upon PolyI:C or R848 stimulation respectively after 20h of culture or not with "positive" tumors previously treated or not with soluble lectins (n = 3 or 4 tumors). Lectin fixation by each tumor cell line (#1 to 4) was illustrated on the left part and color scaling was done per lectin.

Supplementary figure 10: Reversion of DCs' dysfunction upon treatment of tumor cells by specific lectins may rely on modification of the secretome of tumor cells
7 A/ Impact of lectins on tumor cells. Tumor cells (6 in total, 3 with positive (green) impact and 3 with negative (red) impact on both cDC1s and pDCs) were incubated with lectins (WGA, HPA, MAA) for 2h, washed, and further cultured for 20h. Factors known to potentially influence DCs' activation or functionality were then quantified in the supernatants by Luminex (IL1β, IL6, IL8, IL10, MCP1, MIP1α, MIP1β, TGFβ). B/ DCs' cytokine production upon culture with supernatants derived from "negative" tumor cell lines pre-incubated with lectins (WGA, HPA, MAA). PanDCs (mixture of the three DC subsets cDC2s, cDC1s, pDCs) were purified from several HD blood and co-cultured for 20 hours with supernatants derived from tumor lines pre-incubated with lectins (WGA, HPA, MAA).
Tumor cell lines were selected based on their "negative" impact on IL12 and IFNα production by Cdc2s and pDCs respectively. Collected panDCs were stimulated for 5 hours with or without TLR-L (polyI:C or R848) and the production of cytokines was assessed by intracellular cytokine staining using flow cytometry. Frequencies of cytokine-expressing cDC2s and pDCs upon TLR triggering after co-culture in control conditions or tumor-derived supernatants. Results are expressed as percentages of cytokineexpressing cells within the corresponding DC subset. TNFα + pDCs upon R848 after culture (gray and black bars) or not (white bars) with "negative" tumor 9 cells previously treated (gray bars) or not (black bars) with soluble lectins (n = 4 to 7 per group). Results are expressed as percentages of cytokine-expressing cells within each group. Interleaved box & whiskers representation plotting from minimum to maximum. "Control" represent the condition mix DCs without any TLR stimulation. Only significant statistics are shown on graphs. P-values were calculated using mixed-effects model (REML; stars) with Bonferroni's multiple comparisons test, and/or Wilcoxon matched-paired signed rank test (dashed lines). Stars represent a significant difference between the given group and the condition "Mix DCs + tumor cells". *P-value ≤ 0.05, **P-value ≤ 0.01, ***P-value ≤ 0.001, ****P-value ≤ 0.0001.

Supplementary Figure 13: Gating strategy to depict tumor-infiltrating immune cells by multiparametric flow cytometry
Gating strategy to analyze cDC1s and CD3+ and CD8+ T cells within tumor-infiltrating immune cells.

FSC-A and SSC-A parameters allowed the exclusion of cell debris and, after single cells gating using
FSC-A and FSC-H parameters, dead cells were excluded using Live and Dead cell staining. Among total immune CD45 + cells, cDC1s were depicted within Lin -HLA-DR + cells as CD11c + BDCA3 + cells, and T cells identified as CD45+ CD3+ cells among which we further depicted CD8+ T cells.
Representative flow cytometry plots for patient #18.

Supplementary Tables
Suppl Figure 1 Suppl Figure 2